Page 32 - 《水资源与水工程学报》2025年第1期
P. 32

2                        & ' ( ) & * + , -                 2025 $
              8
                 0,2014.                                           ʞðn1’[J]. FZp½cZb#$( 4â[),
            [14]xyy, %&', 9–…, :. p€0µv=>\¹                      2023,21(5):843861+950.
                 AB.Œ[J]. †¸c;<,2019,35(6):3640.              [22]Ùº~, 2 Í, 5 3. %ƒp€0¹{ƒ8iº
            [15]÷˝, ) (. ÕÏÎ@<µ¶( ) 5t)[M]. p                    ³€[J]. Zèl¡AB,2023,30(3):289294.
                 U: 4!N¶a0#t,2019.                            [23]¬ j, 4 :. %ƒÜ.p€0iº{‰p45ƒ„
            [16]SHIRMOHAMMADIB,VAFAKHAHM,MOOSAVIV,                 8ijcZ[µ¶[J]. aø#00n,2023,46(1):
                 etal.Applicationofseveraldatadriventechniquesfor  6981.
                 predictinggroundwaterlevel[J].WaterResourcesMan  [24]9Óp, 5–¸, 5+6. %ƒ MIKESHEiº{XE
                 agement,2013,27:419432.                          JKZhkijAB[J]. N¶IE,2022,44(2):100
            [17]CHENChong,HEWei,HANZhou,etal.Acomparative          105.
                 studyamongmachinelearningandnumericalmodelsfor  [25]78Û, 9. 4BZ%'0( )*t)[M]. pU:
                 simulatinggroundwaterdynamicsintheHeiheRiverBa   4!4Ÿ#t,2010.
                 sin ,northwesternChina[J].ScientificReports,2020,  [26]¹|À, ² ö. 4BZ%'0[M]. ŽÍ: 4!4Ÿa
                 10(1):3904.                                       0#t,1999.
            [18]TAO Hai,HAMEED M M,MARHOON H A,etal.           [27]s ‚, ¹:+, ƒp. é;<ÅC}~qí ARIMA-
                 Groundwaterlevelpredictionusingmachinelearningmod  LSTMÏ@VÑðñ€[J]. Z'8q0n,2023,42
                 els: a comprehensive review[J]. Neurocomputing,   (11):146156.
                 2022,489:271308.                             [28]é[-, ‰==, Ë ”, :. cñ]=ÐÑ45Z[i
            [19]I³[, ) *, +Ȁ. }.%ƒz{0žôЩ³                       jc4SZ]^Ï1µ2³´: Ö(>EJK 
                 ´µŸ¶·{ÊZðn€[J]. êžÃ¾,2024,43                     [J]. 4!—VZbZq,2023(7):818.
                 (1):4553.                                    [29]ZHAOJiwei,NIEGuangzheng,WENYihao.Monthlypre
            [20]¥#¦, œ V, A,-. 89fÂëþÏ1µ2ž¡                       cipitationpredictioninLuoyangCitybasedonEEMD-
                 ÞÂ7[J]. $.c/Yø\,2024,18(1):8188.               LSTM-ARIMAmodel [J].WaterScienceandTechnolo
            [21]¨š©, 9–0, …Ф, :. %ƒp€0iº{íî                      gy ,2023,87(1):318335.

            檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵

                 ( LMA 17 B)

            [21]GRIFFITHSJA,ZHUFangfang,CHANFKS,etal.Model    [24]5úú, )çà, )–O, :. %ƒ AHP ç!{?R
                 lingtheimpactofsealevelriseonurbanfloodprobabilityin  @45ÂZþXY³€ [J]. 4„AB,2020,39
                 SEChina [J].GeoscienceFrontiers,2019,10(2):363372.  (8):18921906.
            [22]CHANGJun,YINZuotang,ZHANG Zhendong,etal.       [25]¿À¶, é+…, ˜rd, :. %ƒ D-S ê„èžÆ
                 Multidisasterintegratedriskassessmentincityrange :a  AHP ç!{JKÂëþ³€AB[J]. Z]^cZ
                 casestudyofJinan ,China[J].InternationalJournalof  CD0n,2024,35(1):916.
                 EnvironmentalResearchandPublicHealth ,2023,20  [26]Zb:ZWþXY:A(3J. ÂZXY5\…
                 (4):3483.                                         †5%´$£W:FXPC/SLP—01[S]. pU: 4!
            [23]ZHAONaizhuo,LIUYing,CAOGuofeng,etal.Fore          ZbZq#t,2021.
                 castingChina’sGDPatthepixellevelusingnighttime  [27]] ^, xPB, ¿À¶, :. *'œž、 Â、 ×Üv¿/
                 lightstimeseriesandpopulationimages [J].GIScience&  ßñ¼Âëµ¶íîiº[J]. Z]^cZCD0n,
                 RemoteSensing ,2017,54(3):407425.                2016,27(5):123129.
   27   28   29   30   31   32   33   34   35   36   37